Product Manager - Supply Planning

Overview

Own product decisions for supply planning in Lyric's enterprise AI platform, translating planner operating knowledge into reusable product capabilities, with demand-planning breadth valuable alongside it.

What you'll do

• Understand planner problems in manufacturing and supply networks, including material and capacity constraints, production, inventory and deployment decisions.
• Translate recurring problems into product requirements and reusable capabilities, distinguishing shared planning patterns from customer-specific configuration.
• Work with planners and engineering to make constraints, scenarios, exceptions and overrides understandable and useful in the product.
• Contribute to prioritization, roadmap choices, validation and adoption, connecting product decisions to the operational outcomes they should improve.
• Explore where AI-assisted planning can reduce manual effort while preserving the explanation and control needed for consequential decisions.

What you'll need

• Prior hands-on experience as a planner, with specific examples of the decisions you owned.
• Experience implementing or working with APS vendors and an understanding of the planning problem beneath the software.
• Relevant progression into consulting, product management or a combination of the two.
• Supply-planning depth relevant to this opening; explain where your strongest expertise lies.
• Ability to connect tools, planning logic and business strategy, and explain why a decision or design should change.
• Clear communication with planners and technical partners, with interest in turning operating expertise into a reusable product.

Nice to have

• A combination of consulting and product experience, taking planning knowledge across multiple customers.
• Experience with constrained planning, production scheduling, deployment, inventory optimization or order promising.
• Examples of a reusable planning model, template, workflow or product capability emerging from recurring customer needs.
• Thoughtful experimentation with AI-assisted planning, including where human review and explanation remain important.

Details

• Location: India.